Determinants of Tax Evasion Behavior

15
Copyright © Canadian Research & Development Center of Sciences and Cultures
ISSN 1923-841X [Print]
ISSN 1923-8428 [Online]
www.cscanada.net
www.cscanada.org
International Business and Management
Vol. 6, No. 2, 2013, pp. 15-23
DOI:10.3968/j.ibm.1923842820130602.1085
Determinants of Tax Evasion Behavior: Empirical Evidence from Survey Data
Gamze Oz Yalama
[a]
; Erdal Gumus
[a],*
[a]
Department of Public Finance, Eskisehir Osmangazi University,
Turkey.
*Corresponding author.
Received 17 March 2013; accepted 5 May 2013
Abstract
Tax revenues are major and important income sources
for governments in most countries. Sufficient tax
revenues make many government projects possible and
help elected officials and politicians to remain in office
longer if the government implements programs and
projects demanded by the public. In today’s globalizing
economic environments, there is increasing demand for
a variety of public services and programs. However, the
rate of increase in the tax revenues to finance these public
services and programs falls short of the necessary public
spending. The potential tax revenue of a country based on
its legal or tax law is much larger than the tax revenues
that are actually collected. Due to the lack of full tax
compliance, government budgets are rarely balanced in
most countries, and the gap between revenue and spending
is increasing. The main question is why taxpayers evade
taxes. To understand tax evasion, one can examine what
factors cause taxpayers to evade taxes. If factors that
affect tax evasion are identified, policies can be developed
to prevent tax evasion.
The purpose of this study is to investigate factors
related to tax evasion behavior using survey data collected
in Turkey. Factor analysis and multiple regression
techniques are employed. The results show that taxational
and fiscal factors, economic factors, demographic factors,
administrative factors, and other factors have statistically
significant effects on tax evasion behavior.
Key words:
Tax evasion; Tax compliance; Individual
behavior; Factor analysis
Gamze Oz Yalama, Erdal Gumus (2013). Determinants of Tax Evasion
Behavior: Empirical Evidence from Survey Data. International
Business and Management, 6(2), 15-23. Available from: http://www.
cscanada.net/index.php/ibm/article/view/j.ibm.1923842820130602.1085
DOI: http://dx.doi.org/10.3968/j.ibm.1923842820130602.1085
INTRODUCTION
Tax revenues are major and important income sources for
governments in most countries. Sufficient tax revenues
make many government projects possible and help elected
officials and politicians to remain in office longer if the
government implements programs and projects demanded
by the public. Additionally, the collection of appropriate
tax revenues can help to stabilize the economy by ensuring
less dependency on government borrowing. In today’s
globalizing economic environments, there is increasing
demand for a variety of public services and programs.
However, the rate of increase in the tax revenues to
finance these public services and programs falls short of
the necessary public spending. The potential tax revenue
of a country based on its legal or tax law is much larger
than the tax revenues that are actually collected. A number
of factors may contribute to the difference between
potential and actual tax revenues. Tax collecting agencies
may demonstrate institutional inefficiencies, inadequate
tax collection capabilities, and personal management
issues. Among taxpayers, many factors may lead to
incomplete tax compliance. Due to the lack of full tax
compliance, government budgets were rarely balanced in
most countries from 2002 to 2010, as shown in Table 1.
France, Greece, Japan, Portugal, the United Kingdom, and
the United States face large budget deficits that were more
than 5 percent of their respective GDPs in 2009 and 2010.
A large budget deficit may not be attributable only to tax
collection, but this may be an important factor.
Determinants of Tax Evasion Behavior: Empirical Evidence from Survey Data
16
Copyright © Canadian Research & Development Center of Sciences and Cultures
Table 1
Cash Surplus/Defcit (Percent of GDP)
Country Name 2002 2003 2004 2005 2006 2007 2008 2009 2010
Brazil -1.17 -4.34 -1.86 -3.59 -2.89 -1.87 -1.21 -3.47 -1.67
Canada 1.55 1.12 1.58 0.82 1.64 1.79 0.60 -1.42 -2.03
France -3.40 -4.13 -3.47 -2.79 -2.18 -2.34 -2.86 -7.26 -6.98
Germany -2.05 -2.22 -2.38 -2.33 -1.28 -0.33 -0.32 -2.24 -3.11
Greece -4.88 -5.80 -7.35 -5.59 -5.93 -6.73 -9.84 -15.80 -10.77
India -4.59 -3.38 -3.20 -3.18 -2.24 -0,47 -4.87 -5.23 -3.77
Italy -2.37 -3.21 -2.59 -3.66 -2.43 -1.42 -2.29 -5.00 -4.04
Japan -4.06 -0.87 -2.44 -2.95 -7.58 -6.73
Korea, Rep. 3.64 1.71 0.10 0.91 1.14 2.32 1.64 0.02 1.65
Portugal -2.49 -2.66 -3.30 -5.52 -3.93 -2.57 -3.20 -9.41 -8.99
Turkey 1.90 1.41 -1.94 -5.55 -2.25
United Kingdom -1.98 -3.51 -3.20 -3.04 -2.74 -2.69 -4.71 -10.98 -10.04
United States -2.60 -3.83 -3.62 -2.76 -1.83 -2.23 -5.29 -10.39 -10.11
Source: World Bank, World Databank, World Development Indicator.
One indicator of insufficient tax collection may be
government debt stock. Many countries have government
debt stocks that are more than 60 percent of their GDPs.
Table 2 reports central government debt stocks as a
percentage of GDP for selected countries. Greece, Italy,
and Japan have debt stocks greater than 100 percent of
their respective GDPs. Furthermore, France, Portugal, the
United Kingdom, and the United States have debt stocks
greater than 50 percent of their GDPs.
Table 2
Central Government Debt Stock (Percent of GDP)
Country Name 2002 2003 2004 2005 2006 2007 2008 2009 2010
France 66 70 71 73 68 67 73 84 88
Germany 39 41 43 45 43 41 43 48 56
Greece 129 124 128 125 128 126 128 144 135
Italy 115 111 111 113 109 104 107 119 117
Japan 144 145 144 153 167 175
Portugal 63 65 67 70 69 68 79 91 94
Turkey 51 44 44 51 51
United Kingdom 41 42 44 46 46 47 57 73 83
United States 43 46 47 47 47 47 55 68 77
Source: World Bank, World Databank, World Development Indicator.
A higher government debt burden limits the government’s
ability to provide various public goods. To avoid this
limitation, tax administrations attempt to fully collect due
taxes. The subject of this study, Turkey’s tax share of its
general government budget from 1990 to 2011, is shown
in Table 3. The average share of tax revenue to general
government spending is approximately 82 percent for the
most recent 22-year period in Turkey. On average, there is a
tax revenue gap of 18 percent from a balanced budget.
Gamze Oz Yalama; Erdal Gumus (2013).
International Business and Management, 6(2), 15-23
17
Copyright © Canadian Research & Development Center of Sciences and Cultures
Table 3
Share of Tax Revenues in General Government Budget
in Turkey (1990 – 2011)*
Years Share Years Share
1990 82 2001 78
1991 82 2002 80
1992 81 2003 86
1993 75 2004 84
1994 79 2005 80
1995 78 2006 83
1996 84 2007 84
1997 83 2008 84
1998 79 2009 84
1999 79 2010 87
2000 80 2011 90
* Composition of general tax revenues are as follows: Between 1990
and 2003 tax revenue, non-tax income, private income and funds,
between 2004 and 2006 tax revenues, non-tax income, capital income,
grants and aids received, between 2006 and 2010 tax revenues, enterprise
and property income, grants and aids received, interest income, shares
and income from fne and capital income.
Source: General Directorate of Revenue, Tax Statistics, http://www.gib.
gov.tr/, Visited: 08/07/2012.
Although the share of tax revenue to the general state
budget is high, it is not sufficient to cover total public
expenditure. There is an enormous gap between the
amount of taxes legally owed (which can be considered
the potential tax amount) and the amount of taxes that the
government actually collects. To obtain insight into the
tax avoidance behavior of taxpayers, one can consider tax
inspection statistics. Table 4 presents brief tax auditing
results from Turkey for 2000 to 2009. The rate of tax
auditing is approximately 2 percent in Turkey when only
income and corporate taxation are considered. The tax base
is shown in column 2, and the difference identified in the
tax base through the auditing process is shown in the third
column. This difference was approximately 267 percent
in 2008, which is the highest number in a recent ten-year
period. In 2008, taxpayers reported a tax base of nearly
79 billion TL; however, inspectors found a 211 billion TL
difference in the tax base in the same year. This means that
the true or potential tax base was 290 billion TL.
Table 4
Results of Tax Audits (2000 – 2009)
Years
Inspected Tax Base*
(000 TL) (1)
Differences Found in
Tax Base* (000 TL) (2)
(2/1)
Percent
GDP (Current Prices)
(000 TL) (3)
Total Tax Revenues
(000 TL)(4)
(4/3)
Percent
2000 3,621,021 1,987,099 54.8 166,658,021 26,503,698 15.9
2001 7,289,622 13,478,317 184.8 240,224,083 39,735,928 16.5
2002 13,863,392 7,971,330 57.4 350,476,089 59,631,868 17.0
2003 25,563,195 18,834,977 73.6 454,780,659 84,316,169 18.5
2004 22,124,052 18,712,916 84.5 559,033,026 101,038,904 18.0
2005 32,548,467 38,715,354 118.9 648,931,712 131,948,778 20.3
2006 46,796,638 47,419,483 101.3 758,390,785 151,271,701 19.4
2007 63,409,073 30,450,980 48.0 843,178,421 171,098,466 20.2
2008 78,838,889 211,092,889 267.7 950,534,251 189,980,827 19.9
2009 125,603,952 97,972,236 78.0 952,558,579 196,313,308 20.6
* Inspection results include audits that have done by tax administration after 2001.
Source: Data have been collected and reconciled by the following web sites (2001 – 2009), http://www.gkd.org.tr/, http://www.gib.gov.tr/, visited:
02/22/2011. GDP (2000-2009), http://www.tuik.gov.tr/, Visited: 04/27/2011. Total Tax Revenue, http://www.gib.gov.tr/fileadmin/user_upload/VI/
GBG/Tablo_1.xls.htm, Visited: 04/27/2011.
Thus, it is clear that one of the most important reasons
for this gap is tax evasion. Tax evasion is a gamble
that pays off in lower taxes or, due to the probability
of detection, ends in sanctions (Torgler, 2003). In other
words, tax evasion is a process that reduces taxpayers’ tax
liability to zero (if possible) by acting against the related
tax law. From the standpoint of the tax authority, it is
important to identify tax evasion behavior by taxpayers.
Knowledge of this information can help the tax authority
to develop policies to prevent tax evasion and collect
sufficient tax revenues.
To understand tax evasion, one can examine the
factors that cause taxpayers to evade taxes; based on this
information, policies can be developed to prevent tax
evasion. This study uses data from a survey conducted in
Turkey to answer the question of which factors contribute
to tax evasion. The rest of this paper is organized as
follows: section 2 reviews the relevant literature, section
3 describes the method and data, section 4 describes the
research results, and section 5 provides conclusions.
Determinants of Tax Evasion Behavior: Empirical Evidence from Survey Data
18
Copyright © Canadian Research & Development Center of Sciences and Cultures
1. BRIEF LITERATURE REVIEW
Many factors have been studied in the literature to explain
the tax evasion behavior of taxpayers. Previous studies
include those by Allingham and Sandmo (1972), Spicer and
Becker (1980), Clotfelter (1983), Feinstein (1991), Kirchler
(1997), Frey and Feld (2002), Torgler (2003), and Feld,
Torgler, and Dong (2008). Some common factors examined
in these studies include tax rates, the tax burden, income
level, source of income, tax audits, tax penalties, public
expenditures, public services, tax mentality, tax morale,
age, gender, marital status, education, the tax system, the
tax administration, bureaucracy, and democracy.
Since the pioneering work of Allingham and Sandmo
(1972), the literature on tax evasion has been significantly
expanded. Allingham and Sandmo (1972) identified
both static and dynamic aspects of tax evasion. They
emphasized the relationship between incentives to avoid
taxes and incentives to supply work effort. Additionally,
they showed that the declared income level depends on
actual income, the tax rate, the penalty rate, and the audit
rate. They explained their finding as follows: “When
actual income varies, the fraction declared increases, stays
constant or decreases according as relative risk aversion is
an increasing, constant or decreasing function of income”
(Allingham & Sandmo, 1972). They concluded that the
substitution effect was negative because an increase in
the tax rate makes it more profitable to evade taxes on
the margin, whereas the income effect is positive because
an increased tax rate makes the taxpayer less wealthy.
Their study showed that an increase in the penalty rate
will always increase the fraction of actual income to be
declared, and an increase in the probability of detection
will always lead to a larger income being declared.
Some papers have stressed that an increase in the
tax rate will result in an increase in the propensity
for tax evasion (Clotfelter, 1983; Crane & Nourzad,
1990; Alm, Jackson & Mc Kee, 1992; Pommerehne &
Weck-Hannemann, 1996; Saracoglu, 2008). A positive
relationship has been identified in the literature between
income level and tax evasion: as individuals’ income
levels increase, their tax evasion behavior also increases
(Crane & Nourzad, 1990; Becker, Büchner & Sleeking,
1987). However, Dubin, Graetz, and Wilde (1990)
conclude that “there is strong direct relationship between
real income per capita and reported taxes per return”, and
the empirical results of Alm, Jackson, and McKee (1992)
indicate that “higher income leads to higher compliance”.
Johns and Slemrod (2008) find that “the ratio of
underreported tax to true tax highest for lower-income
taxpayers”. In other words, lower-income taxpayers
have lower compliance. This finding implies that low-
income earners are likely to hide their income. However,
Feinsten (1991) finds no significant relationship between
income and tax evasion. Richardson (2006) finds that
tax evasion is much lower when the source of income is
from wages and salaries. Spicer and Lundstedt (1976) do
not find a significant relationship among tax evasion, tax
penalties, and the probability of detection. Similarly, Alm,
Jackson, and McKee (1992) do not capture a significant
relationship between the penalty rate and tax evasion.
Bagdigen and Erdogan (2010) emphasize that an increase
in tax penalties leads to a decrease in tax-evading behavior
by taxpayers.
From the perspective of tax auditing, it is clear that an
increase in tax audits leads to a decrease in tax evasion
(Alm, Jackson and McKee, 1992; Alm, McClelland and
Schulze, 1992). Gemmell and Ratto (2012) investigate
the relationship between random audits and taxpayers’
responses by comparing randomly selected audited and
non-audited taxpayers. These authors conclude that
audited taxpayers have reduced subsequent compliance. In
their study, Snow and Warren Jr. (2005) conclude that an
increase in tax audits and tax penalties leads to an increase
in tax evasion. Becker, Büchner, and Sleeking (1987)
show that an increase in the percentage of public transfer
expenditures leads to a decrease in tax evasion.
Buehn and Schneider (2012) developed a time series
of the tax evasion for 38 OECD countries between 1999
and 2010. In their study, these authors consider indirect
taxation and self-employment as the driving forces of tax
evasion. They find that the average level of tax evasion for
38 OECD countries in 2010 was 2.8 percent. The highest
tax evasion level was found in Mexico (6.8 percent) over
the 1999-2010 period, followed by Turkey (6.7 percent),
Romania (6.0 percent), and Bulgaria (5.7 percent). The
United States had the lowest tax evasion level (0.5 percent).
Tax mentality, tax morale, civic duty, and law-abiding
citizens affect levels of tax evasion. For example, Kirchler
(1997) and Feld, Torgler, and Dong (2008) stressed that
a positive tax mentality and tax morale have a negative
effect on tax evasion.
Dell’Anno (2009) reports that tax morale is
dependent on taxpayers’ intrinsic attitudes toward
honesty and social stigma. Social stigma represents
the reputational cost. A decrease in reputational cost
tends to increase tax evasion. Dulleck et al. (2012)
conduct an experiment using heart rate signals to
analyze the relationship between psychic cost (for
instance, feelings of guilt) and tax compliance. They
find a positive relationship between psychic cost and
tax compliance. Bayrakli, Saruc, and Sagbas (2004)
show that when tax-evading behavior is known by
other people, the resulting embarrassment cost tends
to decrease tax evasion.
The effect of demographic factors on tax evasion
is controversial in the literature. Some studies provide
empirical evidence of a significant relationship
between demographic factors and tax evasion, whereas
other studies do not find a significant relationship.
For example, Spicer and Becker (1980) show that
Gamze Oz Yalama; Erdal Gumus (2013).
International Business and Management, 6(2), 15-23
19
Copyright © Canadian Research & Development Center of Sciences and Cultures
male taxpayers tend to evade taxes more than female
taxpayers. McGee and Tyler (2006) stress that tax
evasion is more unacceptable behavior for female
taxpayers than for male taxpayers. Feinstein (1991)
emphasizes that individuals who have their own
business are much more likely to evade taxes than the
average taxpayer. He also finds that individuals who
are 65 years or older are less likely to evade taxes and
that married individuals are more likely to evade taxes.
Frey and Feld (2002) study the relationship between
tax morale and tax officials’ behavior in the context of tax
evasion. They find that when tax officials are respectful
in their duties toward taxpayers, tax morale increases.
Richardson (2006) studies the relationship between tax
evasion and the complexity of the tax structure. He finds
that the lower the level of complexity, the lower the level
of tax evasion is across countries. Riahi-Belkaoui (2008)
studies bureaucracy and tax behavior and concludes that
an increase in bureaucracy leads to an increase in tax
evasion. In sum, many factors contribute to or affect the
tax-evading behavior of taxpayers. However, the degree
of each factor’s effect on the tax-evading behavior of
taxpayers may differ due to differences in cultural and
institutional settings.
2. METHOD AND DATA
In this section, we introduce our data and perform the
necessary tests. Then, we use factor analysis and run
multiple regressions.
To study the tax evasion behavior of taxpayers
in Turkey, we conducted a survey in the province
of Eskisehir. The survey sample consisted of 500
randomly selected taxpayers. Surveys were distributed
in the summer of 2010. Of the 500 surveys distributed,
420 were returned, for a response rate of 84 percent.
The sample comprised small, medium and large
corporations, workers who received wages from these
companies, public institutions, offices owned by self-
employed persons, and small traders. The survey
included two sections and 37 questions. The first
section consisted of questions about the demographic
characteristics of the taxpayers, and the second section
included statements related to the tax evasion behavior
of taxpayers. Thirty statements were presented in the
second section, and respondents were asked to rate the
importance of each statement using a five-point Likert
scale (1 = least important; 5 = most important).
The demographic characteristics are reported in Table
5. Of the total sample in the study, most of the respondents
were male (70.53 percent). Approximately half of the
subjects were in the 40- to 50-year-old age range (56.6
percent), 21 percent were younger than 30 years old, and
22.5 percent were between 51 and 71+ years old.
Table 5
Participants’ Demographic Characteristics
Demographic Variables Defnition Frequency Percentage
Age 10-20
21-30
31-40
41-50
51-60
61-70
71+
Male
Female
Married
Single
Divorced
Widowed
Separated
8
76
89
137
74
14
2
282
118
292
89
9
9
1
2.0
19.0
22.3
34.3
18.5
3.5
0.5
70.5
29.5
73.0
22.3
2.3
2.3
0.3
Gender
Marital Status
Number of Child
None
1
2
3
4+
110
87
142
54
7
27.5
21.8
35.5
13.5
1.8
Social characteristics are reported in Table 6.
The incomes of the respondents ranged from 601
TL to 2500 TL per month (64.8 percent). Regarding
education level, 33 percent of the respondents had a
university degree, 3.1 percent were post-graduates,
21.3 percent had an upper-school degree, 41.3 percent
had secondary school education, and 1.5 percent had
obtained a primary school diploma.
Table 6
Participants’ Social Characteristics
Demographic
Variables
Defnition Frequency Percentage
Diploma Earned Primary Sch.
Secondary Sch.
High School
Upper Sch.
University
Master
PhD.
6
32
133
85
132
11
1
1.5
8.0
33.3
21.3
33.0
2.8
0.3
Occupation Businessman
Industrialist
Small Traders
Public Offcials
Farmers
Self Employed
Renter
Worker
Others
20
22
86
106
8
69
7
41
41
5.0
5.5
21.5
26.5
2.0
17.3
1.8
10.3
10.3
Income Level (TL) Less than 600
601-1500
1501-2500
2501-5000
5001-10000
10001-20000
20001-50000
50001-100000
100001-200000
200001 +
27
153
106
37
22
21
18
11
4
1
6.8
38.3
26.5
9.3
5.5
5.3
4.5
2.8
1.0
0.3
Determinants of Tax Evasion Behavior: Empirical Evidence from Survey Data
20
Copyright © Canadian Research & Development Center of Sciences and Cultures
The taxpayers consisted of two types of individuals: 49
percent were wage and salary earners, and the remaining
51 percent owned their own businesses.
We performed a Cronbach’s alpha test on our data and
obtained a coefficient of 0.775 for all 30 items. All of the
scale’s reliability values were well above 0.70, indicating
a satisfactory level of internal consistency among the
items in the study. Consequently, the reliability and
validity of the measurement model were satisfactory.
2.1 Factor Analysis
To apply factor analysis, it was necessary to test the
Kaiser-Meyer-Olkin (KMO) measure of sampling
adequacy (Zhang et al., 2003). This test result is shown
in Table 7. For the attitude variables, the KMO value
was 0.798, which indicates that the sample was adequate
for factor analysis (Kaiser, 1974). The Bartlett Test
for Sphericity (BTS) is also reported in Table 7. This
test result was 3183.308 (p <.001), which confirms the
adequacy of using factor analysis.
Table 7
KMO and Bartlett’s Test of Sphericity
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.798
Bartlett’s Test of Sphericity Approx. Chi-Square 3183.308
df 435
Sig. 0.000
Orthogonal rotation (varimax) was chosen for the
exploratory factor analysis. As Hair, Anderson, Tatham,
and Black (1995) note, orthogonal extraction with varimax
rotation is appropriate for the research purposes and the
need to reduce a large number of variables to a small set
of uncorrelated variables. The purpose of varimax rotation
is to minimize the number of variables that have high
loadings on a factor, which enhances the interpretability
of the factors (Kim & Mueller, 1978).
According to the principal component analysis, eight
factors had an eigenvalue equal to or greater than 1.0,
explaining a total of 56.761 percent of the variance, as
shown in Table 8.
Table 8
Total Variance Explained*
Initial Eigen Values Extraction Sums of Squares Loadings Rotation Sums of Squared Loadings
Total Total Percent of Variance Cumulative Percent Total Percent of Variance Cumulative Percent
1 4.285 4.285 14.282 14.282 3.328 11.093 11.093
2 4.186 4.186 13.952 28.234 2.676 8.919 20.013
3 2.293 2.293 7.644 35.878 2.527 8.423 28.436
4 1.540 1.540 5.134 41.012 2.344 7.812 36.248
5 1.358 1.358 4.528 45.540 1.775 5.915 42.163
6 1.197 1.197 3.991 49.530 1.568 5.226 47.388
7 1.116 1.116 3.721 53.252 1.541 5.136 52.525
8 1.053 1.053 3.510 56.761 1.271 4.237 56.761
*Other variables’ (from 9 to 30) initial eigen values (total) change between 0.919 and 0.280.
Based on the factor loadings, we classified and named the factors shown below.
Tax Evasion Factor (contained three items, such as tax
morality, tax mentality).
Taxational and Fiscal Factors (contained eight items,
such as tax rate, tax burden).
Economic Factors (contained six items, such as
rational behavior, cost and benefit, utility maximization)
Demographic Factors (contained four items, such as
gender, age).
Politic Factors (contained three items, such as
democracy, fair income distribution).
Administrative Factors (contained two items, such as
tax penalties, tax audits).
Mixed Factors (contained five items, such as income
level, income components).
Additional Factors (contained two items, such as
informal economy).
All loading estimates were significant (p<0.01),
ranging from a low of 0.40 to a high of 0.84.
Gamze Oz Yalama; Erdal Gumus (2013).
International Business and Management, 6(2), 15-23
21
Copyright © Canadian Research & Development Center of Sciences and Cultures
Table 9
Factor Loadings
Factors
1 2 3 4 5 6 7 8
t1 0.784
t2 0.842
t3 0.800
t4 0.463
t5 0.753
t6 0.755
t7 0.693
t8 0.711
t9 0.694
t10 0.537 0.428
t11 0.781
t12 0.602
t13 0.458
t14 0.462 0.411
t15 0.642
t16
t17 0.419 -0.406
t18 0.794
t19 0.793
t20 0.616
t21 0.443 0.646
t22 0.428 0.483
t23 0.518
t24 0.485
t25 0.467
t26 0.650
t27 0.629
t28
t29 0.748
t30 0.618
2.2 Regression Analysis
After the factor analysis, we ran a regression using
the factors as variables to identify their effect on tax
evasion. In addition to these factors, we also used gender,
income, education, marital status, and age as independent
variables. We used an equation in the following form:
TE = β
0
+ β
j
X
j
+ ε.
In this equation, TE is the dependent variable, called tax
evasion, and X
j
represents the independent variables. There
are 12 independent variables: taxational and fiscal factors
(X
1
), economic factors (X
2
), demographic factors (X
3
),
political factors (X
4
), administrative factors (X
5
), mixed
factors (X
6
), additional factors (X
7
), gender (X
8
), income
(X
9
), education (X
10
), marital status (X
11
), and age (X
12
).
We tested our data for heteroscedasticity using the
Ljung-Box Q_((n))^2 test statistic for the nth lag. The test
statistics were lower than the critical values (0.0000<0.01).
Consequently, the null hypothesis was rejected. We follow
White’s (1980, 1986) correction procedure to increase
the efficiency of our estimation and used the Ramsey-
RESET Stability Test. The results showed that there was
no misspecification in the model.
3. RESULTS
Our regression results are presented in Table 10. Our
results show that economic, demographic, administrative,
and additional factors are statistically significant. There is
a positive relationship between tax evasion and taxational
and fiscal factors. This result indicates that increases in
the tax rate and in the tax burden increase tax evasion.
This result supports the studies by Clotfelter (1983),
Crane and Nourzad (1990), Alm, Jackson, and McKee
(1992), Pommereehne and Weck-Hannemann (1996),
and Saracoglu (2008). We find a positive relationship
between administrative factors and tax evasion, which is
in accordance with the findings by Snow and Warren Jr.
(2005). Economic factors have negative and statistically
significant effects on tax evasion.
Table 10
Coeffcients
Model Understandardized Coeffcients Standardized t Sig.
B Std. Error Coeffcients Beta
(Constant) 1.499 0.323 4.640 0.000
Taxational and Fiscal Factors (X1) 0.087 0.048 0.087 1.820 0.070*
Economic Factors (X2) -0.135 0.049 -0.135 -2.749 0.006***
Demographic Factors (X3) -0.113 0.050 -0.113 -2.272 0.024**
Politic Factors (X4) 0.057 0.047 0.057 1.218 0.224
Administrative Factors (X5) 0.121 0.049 0.121 2.461 0.014**
Mixed Factors (X6) 0.032 0.047 0.032 0.686 0.493
To be continued
Determinants of Tax Evasion Behavior: Empirical Evidence from Survey Data
22
Copyright © Canadian Research & Development Center of Sciences and Cultures
Model Understandardized Coeffcients Standardized t Sig.
B Std. Error Coeffcients Beta
Additional Factors (X7) -0.140 0.049 -0.140 -2.834 0.005***
Gender (X8) -0.149 0.108 -0.068 -1.379 0.169
Income (X9) -0.219 0.036 -0.396 -6.074 0.000***
Education (X10) -0.133 0.047 -0.147 -2.842 0.005***
Marital Status (X11) 0.088 0.076 0.058 1.158 0.248
Age (X12) -0.057 0.049 -0.067 -1.155 0.249
R
2
= 0.168 F = 6.506 (prob. 0.000), ***Statistically signifcant at p = 0.01,
** Statistically signifcant at p = 0.05, * Statistically signifcant at p = 0.10
Continued
Education also has a negative effect on tax evasion.
This finding can be interpreted as indicating that those
taxpayers who have less education tend to evade taxes
more often than higher-educated taxpayers. With regard
to income level, there is a negative effect on tax evasion.
As income increases, taxpayers show tax compliance
behavior rather than showing tax-evading behavior. As
Alm, Jackson, and McKee (1992) note, “Higher income
leads to higher compliance”.
CONCLUSIONS
In many countries, there is an enormous gap between the
amount of taxes legally owed and the amount of taxes that
taxpayers report and pay. One of the reasons for this gap
may be different tendencies in the tax evasion behavior of
taxpayers. The results of this study show that taxational
and fiscal factors, economic factors, demographic
factors, administrative factors, and additional factors
are statistically significant for individuals’ tax-evasion
behavior. These findings may be useful to policy makers
and researchers. Specifically, tax authorities should design
policies to help increase the income level of taxpayers
rather than increasing administrative measures toward
taxpayers. This may lead to higher tax compliance in
the long run. Our findings contribute to the literature
by providing additional evidence on the factors related
to tax evasion. However, the data used in this study
were collected in only one city. Further studies may be
conducted to obtain more supportive evidence by using a
multi-city analysis.
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